1 Data preparation

1.1 Outline

  • Load scripts: loads libraries and useful scripts used in the analyses; all .R files contained in scripts at the root of the factory are automatically loaded

  • Load data: imports datasets, and may contain some ad hoc changes to the data such as specific data cleaning (not used in other reports), new variables used in the analyses, etc.

1.2 Load packages


library(reportfactory)
library(here)
library(rio) 
library(tidyverse)
library(incidence)
library(distcrete)
library(epitrix)
library(earlyR)
library(projections)
library(linelist)
library(remotes)
library(janitor)
library(kableExtra)
library(DT)
library(cyphr)
library(chngpt)
library(lubridate)
library(ggpubr)
library(ggnewscale)

1.3 Load scripts

These scripts will load:

  • all scripts stored as .R files inside /scripts/
  • all scripts stored as .R files inside /src/

These scripts also contain routines to access the latest clean encrypted data (see next section).


reportfactory::rfh_load_scripts()

1.4 Load clean data

We import the latest NHS pathways data:


x <- import_pathways() %>%
  as_tibble()
x
## # A tibble: 178,928 x 11
##    site_type date       sex   age   ccg_code ccg_name count postcode nhs_region
##    <chr>     <date>     <chr> <chr> <chr>    <chr>    <int> <chr>    <chr>     
##  1 111       2020-03-18 fema… miss… e380000… nhs_glo…     1 gl34fe   South West
##  2 111       2020-03-18 fema… miss… e380001… nhs_sou…     1 ne325nn  North Eas…
##  3 111       2020-03-18 fema… 0-18  e380000… nhs_air…     8 bd57jr   North Eas…
##  4 111       2020-03-18 fema… 0-18  e380000… nhs_ash…     7 tn254ab  South East
##  5 111       2020-03-18 fema… 0-18  e380000… nhs_bar…    35 rm13ae   London    
##  6 111       2020-03-18 fema… 0-18  e380000… nhs_bar…     9 n111np   London    
##  7 111       2020-03-18 fema… 0-18  e380000… nhs_bar…    11 s752py   North Eas…
##  8 111       2020-03-18 fema… 0-18  e380000… nhs_bas…    19 ss143hg  East of E…
##  9 111       2020-03-18 fema… 0-18  e380000… nhs_bas…     6 dn227xf  North Eas…
## 10 111       2020-03-18 fema… 0-18  e380000… nhs_bat…     9 ba25rp   South West
## # … with 178,918 more rows, and 2 more variables: day <int>, weekday <fct>

We also import demographics data for NHS regions in England, used later in our analysis:


path <- here::here("data", "csv", "nhs_region_population_2018.csv")
nhs_region_pop <- rio::import(path) %>%
  mutate(nhs_region = str_to_title(gsub("_"," ",nhs_region)))

nhs_region_pop$nhs_region <- gsub(" Of ", " of ", nhs_region_pop$nhs_region)
nhs_region_pop$nhs_region <- gsub(" And ", " and ", nhs_region_pop$nhs_region)
nhs_region_pop
##                  nhs_region variable      value
## 1                North West     0-18 0.22538599
## 2  North East and Yorkshire     0-18 0.21876449
## 3                  Midlands     0-18 0.22564656
## 4           East of England     0-18 0.22810783
## 5                    London     0-18 0.23764782
## 6                South East     0-18 0.22458811
## 7                South West     0-18 0.20799797
## 8                North West    19-69 0.64274078
## 9  North East and Yorkshire    19-69 0.64437753
## 10                 Midlands    19-69 0.63876675
## 11          East of England    19-69 0.63034229
## 12                   London    19-69 0.67820084
## 13               South East    19-69 0.63267336
## 14               South West    19-69 0.63176131
## 15               North West   70-120 0.13187323
## 16 North East and Yorkshire   70-120 0.13685797
## 17                 Midlands   70-120 0.13558669
## 18          East of England   70-120 0.14154988
## 19                   London   70-120 0.08415135
## 20               South East   70-120 0.14273853
## 21               South West   70-120 0.16024072

Finally, we import publically available deaths per NHS region:


dth <- import_deaths() %>%
  mutate(nhs_region = str_to_title(gsub("_"," ",nhs_region)))

#truncation to account for reporting delay
delay_max <- 21

dth$nhs_region <- gsub(" Of ", " of ", dth$nhs_region)
dth$nhs_region <- gsub(" And ", " and ", dth$nhs_region)
dth
##     date_report               nhs_region deaths
## 1    2020-03-01          East of England      0
## 2    2020-03-02          East of England      1
## 3    2020-03-03          East of England      0
## 4    2020-03-04          East of England      0
## 5    2020-03-05          East of England      0
## 6    2020-03-06          East of England      1
## 7    2020-03-07          East of England      0
## 8    2020-03-08          East of England      0
## 9    2020-03-09          East of England      1
## 10   2020-03-10          East of England      0
## 11   2020-03-11          East of England      0
## 12   2020-03-12          East of England      0
## 13   2020-03-13          East of England      1
## 14   2020-03-14          East of England      2
## 15   2020-03-15          East of England      2
## 16   2020-03-16          East of England      1
## 17   2020-03-17          East of England      1
## 18   2020-03-18          East of England      5
## 19   2020-03-19          East of England      4
## 20   2020-03-20          East of England      2
## 21   2020-03-21          East of England     11
## 22   2020-03-22          East of England     12
## 23   2020-03-23          East of England     11
## 24   2020-03-24          East of England     19
## 25   2020-03-25          East of England     26
## 26   2020-03-26          East of England     36
## 27   2020-03-27          East of England     38
## 28   2020-03-28          East of England     28
## 29   2020-03-29          East of England     43
## 30   2020-03-30          East of England     45
## 31   2020-03-31          East of England     70
## 32   2020-04-01          East of England     62
## 33   2020-04-02          East of England     65
## 34   2020-04-03          East of England     80
## 35   2020-04-04          East of England     71
## 36   2020-04-05          East of England     76
## 37   2020-04-06          East of England     71
## 38   2020-04-07          East of England     93
## 39   2020-04-08          East of England    111
## 40   2020-04-09          East of England     87
## 41   2020-04-10          East of England     74
## 42   2020-04-11          East of England     92
## 43   2020-04-12          East of England    100
## 44   2020-04-13          East of England     78
## 45   2020-04-14          East of England     61
## 46   2020-04-15          East of England     82
## 47   2020-04-16          East of England     74
## 48   2020-04-17          East of England     86
## 49   2020-04-18          East of England     64
## 50   2020-04-19          East of England     67
## 51   2020-04-20          East of England     67
## 52   2020-04-21          East of England     75
## 53   2020-04-22          East of England     67
## 54   2020-04-23          East of England     49
## 55   2020-04-24          East of England     66
## 56   2020-04-25          East of England     54
## 57   2020-04-26          East of England     48
## 58   2020-04-27          East of England     46
## 59   2020-04-28          East of England     58
## 60   2020-04-29          East of England     32
## 61   2020-04-30          East of England     45
## 62   2020-05-01          East of England     49
## 63   2020-05-02          East of England     29
## 64   2020-05-03          East of England     41
## 65   2020-05-04          East of England     19
## 66   2020-05-05          East of England     36
## 67   2020-05-06          East of England     31
## 68   2020-05-07          East of England     33
## 69   2020-05-08          East of England     33
## 70   2020-05-09          East of England     29
## 71   2020-05-10          East of England     22
## 72   2020-05-11          East of England     18
## 73   2020-05-12          East of England     21
## 74   2020-05-13          East of England     27
## 75   2020-05-14          East of England     26
## 76   2020-05-15          East of England     19
## 77   2020-05-16          East of England     26
## 78   2020-05-17          East of England     17
## 79   2020-05-18          East of England     25
## 80   2020-05-19          East of England     15
## 81   2020-05-20          East of England     26
## 82   2020-05-21          East of England     21
## 83   2020-05-22          East of England     13
## 84   2020-05-23          East of England     12
## 85   2020-05-24          East of England     17
## 86   2020-05-25          East of England     25
## 87   2020-05-26          East of England     14
## 88   2020-05-27          East of England     12
## 89   2020-05-28          East of England     17
## 90   2020-05-29          East of England     16
## 91   2020-05-30          East of England      9
## 92   2020-05-31          East of England      8
## 93   2020-06-01          East of England     17
## 94   2020-06-02          East of England     14
## 95   2020-06-03          East of England     10
## 96   2020-06-04          East of England      7
## 97   2020-06-05          East of England     14
## 98   2020-06-06          East of England      5
## 99   2020-06-07          East of England      9
## 100  2020-06-08          East of England      7
## 101  2020-06-09          East of England      6
## 102  2020-06-10          East of England      8
## 103  2020-06-11          East of England      1
## 104  2020-06-12          East of England      9
## 105  2020-06-13          East of England      5
## 106  2020-06-14          East of England      4
## 107  2020-06-15          East of England      8
## 108  2020-06-16          East of England      3
## 109  2020-06-17          East of England      7
## 110  2020-06-18          East of England      4
## 111  2020-06-19          East of England      7
## 112  2020-06-20          East of England      4
## 113  2020-06-21          East of England      3
## 114  2020-06-22          East of England      6
## 115  2020-06-23          East of England      5
## 116  2020-06-24          East of England      4
## 117  2020-06-25          East of England      1
## 118  2020-06-26          East of England      5
## 119  2020-06-27          East of England      6
## 120  2020-06-28          East of England      8
## 121  2020-06-29          East of England      4
## 122  2020-06-30          East of England      5
## 123  2020-07-01          East of England      2
## 124  2020-07-02          East of England      5
## 125  2020-07-03          East of England      0
## 126  2020-07-04          East of England      3
## 127  2020-07-05          East of England      1
## 128  2020-07-06          East of England      2
## 129  2020-07-07          East of England      2
## 130  2020-07-08          East of England      0
## 131  2020-07-09          East of England      8
## 132  2020-07-10          East of England      4
## 133  2020-07-11          East of England      2
## 134  2020-07-12          East of England      1
## 135  2020-07-13          East of England      6
## 136  2020-07-14          East of England      1
## 137  2020-07-15          East of England      0
## 138  2020-03-01                   London      0
## 139  2020-03-02                   London      0
## 140  2020-03-03                   London      0
## 141  2020-03-04                   London      0
## 142  2020-03-05                   London      0
## 143  2020-03-06                   London      1
## 144  2020-03-07                   London      0
## 145  2020-03-08                   London      0
## 146  2020-03-09                   London      1
## 147  2020-03-10                   London      0
## 148  2020-03-11                   London      5
## 149  2020-03-12                   London      6
## 150  2020-03-13                   London     10
## 151  2020-03-14                   London     13
## 152  2020-03-15                   London      9
## 153  2020-03-16                   London     15
## 154  2020-03-17                   London     23
## 155  2020-03-18                   London     27
## 156  2020-03-19                   London     25
## 157  2020-03-20                   London     44
## 158  2020-03-21                   London     49
## 159  2020-03-22                   London     54
## 160  2020-03-23                   London     63
## 161  2020-03-24                   London     86
## 162  2020-03-25                   London    112
## 163  2020-03-26                   London    129
## 164  2020-03-27                   London    129
## 165  2020-03-28                   London    122
## 166  2020-03-29                   London    145
## 167  2020-03-30                   London    149
## 168  2020-03-31                   London    181
## 169  2020-04-01                   London    202
## 170  2020-04-02                   London    191
## 171  2020-04-03                   London    196
## 172  2020-04-04                   London    230
## 173  2020-04-05                   London    195
## 174  2020-04-06                   London    197
## 175  2020-04-07                   London    220
## 176  2020-04-08                   London    238
## 177  2020-04-09                   London    206
## 178  2020-04-10                   London    170
## 179  2020-04-11                   London    178
## 180  2020-04-12                   London    158
## 181  2020-04-13                   London    166
## 182  2020-04-14                   London    143
## 183  2020-04-15                   London    142
## 184  2020-04-16                   London    140
## 185  2020-04-17                   London    100
## 186  2020-04-18                   London    101
## 187  2020-04-19                   London    103
## 188  2020-04-20                   London     95
## 189  2020-04-21                   London     94
## 190  2020-04-22                   London    109
## 191  2020-04-23                   London     77
## 192  2020-04-24                   London     71
## 193  2020-04-25                   London     58
## 194  2020-04-26                   London     53
## 195  2020-04-27                   London     51
## 196  2020-04-28                   London     44
## 197  2020-04-29                   London     45
## 198  2020-04-30                   London     40
## 199  2020-05-01                   London     41
## 200  2020-05-02                   London     41
## 201  2020-05-03                   London     36
## 202  2020-05-04                   London     30
## 203  2020-05-05                   London     25
## 204  2020-05-06                   London     37
## 205  2020-05-07                   London     37
## 206  2020-05-08                   London     30
## 207  2020-05-09                   London     23
## 208  2020-05-10                   London     26
## 209  2020-05-11                   London     18
## 210  2020-05-12                   London     18
## 211  2020-05-13                   London     17
## 212  2020-05-14                   London     20
## 213  2020-05-15                   London     18
## 214  2020-05-16                   London     14
## 215  2020-05-17                   London     15
## 216  2020-05-18                   London     10
## 217  2020-05-19                   London     14
## 218  2020-05-20                   London     19
## 219  2020-05-21                   London     12
## 220  2020-05-22                   London     10
## 221  2020-05-23                   London      6
## 222  2020-05-24                   London      7
## 223  2020-05-25                   London      9
## 224  2020-05-26                   London     13
## 225  2020-05-27                   London      7
## 226  2020-05-28                   London      8
## 227  2020-05-29                   London      7
## 228  2020-05-30                   London     12
## 229  2020-05-31                   London      6
## 230  2020-06-01                   London     10
## 231  2020-06-02                   London      8
## 232  2020-06-03                   London      6
## 233  2020-06-04                   London      8
## 234  2020-06-05                   London      4
## 235  2020-06-06                   London      0
## 236  2020-06-07                   London      5
## 237  2020-06-08                   London      5
## 238  2020-06-09                   London      4
## 239  2020-06-10                   London      7
## 240  2020-06-11                   London      5
## 241  2020-06-12                   London      3
## 242  2020-06-13                   London      3
## 243  2020-06-14                   London      3
## 244  2020-06-15                   London      1
## 245  2020-06-16                   London      2
## 246  2020-06-17                   London      1
## 247  2020-06-18                   London      2
## 248  2020-06-19                   London      5
## 249  2020-06-20                   London      3
## 250  2020-06-21                   London      4
## 251  2020-06-22                   London      2
## 252  2020-06-23                   London      1
## 253  2020-06-24                   London      4
## 254  2020-06-25                   London      3
## 255  2020-06-26                   London      2
## 256  2020-06-27                   London      1
## 257  2020-06-28                   London      2
## 258  2020-06-29                   London      2
## 259  2020-06-30                   London      1
## 260  2020-07-01                   London      2
## 261  2020-07-02                   London      2
## 262  2020-07-03                   London      2
## 263  2020-07-04                   London      1
## 264  2020-07-05                   London      3
## 265  2020-07-06                   London      2
## 266  2020-07-07                   London      1
## 267  2020-07-08                   London      3
## 268  2020-07-09                   London      4
## 269  2020-07-10                   London      0
## 270  2020-07-11                   London      0
## 271  2020-07-12                   London      0
## 272  2020-07-13                   London      1
## 273  2020-07-14                   London      0
## 274  2020-07-15                   London      0
## 275  2020-03-01                 Midlands      0
## 276  2020-03-02                 Midlands      0
## 277  2020-03-03                 Midlands      1
## 278  2020-03-04                 Midlands      0
## 279  2020-03-05                 Midlands      0
## 280  2020-03-06                 Midlands      0
## 281  2020-03-07                 Midlands      0
## 282  2020-03-08                 Midlands      2
## 283  2020-03-09                 Midlands      1
## 284  2020-03-10                 Midlands      0
## 285  2020-03-11                 Midlands      2
## 286  2020-03-12                 Midlands      6
## 287  2020-03-13                 Midlands      5
## 288  2020-03-14                 Midlands      4
## 289  2020-03-15                 Midlands      5
## 290  2020-03-16                 Midlands     11
## 291  2020-03-17                 Midlands      8
## 292  2020-03-18                 Midlands     13
## 293  2020-03-19                 Midlands      8
## 294  2020-03-20                 Midlands     28
## 295  2020-03-21                 Midlands     13
## 296  2020-03-22                 Midlands     31
## 297  2020-03-23                 Midlands     33
## 298  2020-03-24                 Midlands     41
## 299  2020-03-25                 Midlands     48
## 300  2020-03-26                 Midlands     64
## 301  2020-03-27                 Midlands     72
## 302  2020-03-28                 Midlands     89
## 303  2020-03-29                 Midlands     92
## 304  2020-03-30                 Midlands     90
## 305  2020-03-31                 Midlands    123
## 306  2020-04-01                 Midlands    140
## 307  2020-04-02                 Midlands    142
## 308  2020-04-03                 Midlands    124
## 309  2020-04-04                 Midlands    151
## 310  2020-04-05                 Midlands    164
## 311  2020-04-06                 Midlands    140
## 312  2020-04-07                 Midlands    123
## 313  2020-04-08                 Midlands    186
## 314  2020-04-09                 Midlands    139
## 315  2020-04-10                 Midlands    127
## 316  2020-04-11                 Midlands    142
## 317  2020-04-12                 Midlands    139
## 318  2020-04-13                 Midlands    120
## 319  2020-04-14                 Midlands    116
## 320  2020-04-15                 Midlands    147
## 321  2020-04-16                 Midlands    102
## 322  2020-04-17                 Midlands    118
## 323  2020-04-18                 Midlands    115
## 324  2020-04-19                 Midlands     92
## 325  2020-04-20                 Midlands    107
## 326  2020-04-21                 Midlands     86
## 327  2020-04-22                 Midlands     78
## 328  2020-04-23                 Midlands    103
## 329  2020-04-24                 Midlands     79
## 330  2020-04-25                 Midlands     72
## 331  2020-04-26                 Midlands     81
## 332  2020-04-27                 Midlands     74
## 333  2020-04-28                 Midlands     68
## 334  2020-04-29                 Midlands     53
## 335  2020-04-30                 Midlands     56
## 336  2020-05-01                 Midlands     64
## 337  2020-05-02                 Midlands     51
## 338  2020-05-03                 Midlands     52
## 339  2020-05-04                 Midlands     61
## 340  2020-05-05                 Midlands     59
## 341  2020-05-06                 Midlands     59
## 342  2020-05-07                 Midlands     48
## 343  2020-05-08                 Midlands     34
## 344  2020-05-09                 Midlands     37
## 345  2020-05-10                 Midlands     42
## 346  2020-05-11                 Midlands     33
## 347  2020-05-12                 Midlands     45
## 348  2020-05-13                 Midlands     40
## 349  2020-05-14                 Midlands     38
## 350  2020-05-15                 Midlands     40
## 351  2020-05-16                 Midlands     34
## 352  2020-05-17                 Midlands     31
## 353  2020-05-18                 Midlands     36
## 354  2020-05-19                 Midlands     35
## 355  2020-05-20                 Midlands     36
## 356  2020-05-21                 Midlands     32
## 357  2020-05-22                 Midlands     27
## 358  2020-05-23                 Midlands     34
## 359  2020-05-24                 Midlands     20
## 360  2020-05-25                 Midlands     26
## 361  2020-05-26                 Midlands     33
## 362  2020-05-27                 Midlands     29
## 363  2020-05-28                 Midlands     28
## 364  2020-05-29                 Midlands     20
## 365  2020-05-30                 Midlands     21
## 366  2020-05-31                 Midlands     22
## 367  2020-06-01                 Midlands     20
## 368  2020-06-02                 Midlands     22
## 369  2020-06-03                 Midlands     24
## 370  2020-06-04                 Midlands     16
## 371  2020-06-05                 Midlands     21
## 372  2020-06-06                 Midlands     20
## 373  2020-06-07                 Midlands     17
## 374  2020-06-08                 Midlands     16
## 375  2020-06-09                 Midlands     18
## 376  2020-06-10                 Midlands     15
## 377  2020-06-11                 Midlands     13
## 378  2020-06-12                 Midlands     12
## 379  2020-06-13                 Midlands      6
## 380  2020-06-14                 Midlands     18
## 381  2020-06-15                 Midlands     12
## 382  2020-06-16                 Midlands     15
## 383  2020-06-17                 Midlands     11
## 384  2020-06-18                 Midlands     15
## 385  2020-06-19                 Midlands     10
## 386  2020-06-20                 Midlands     15
## 387  2020-06-21                 Midlands     14
## 388  2020-06-22                 Midlands     14
## 389  2020-06-23                 Midlands     16
## 390  2020-06-24                 Midlands     15
## 391  2020-06-25                 Midlands     18
## 392  2020-06-26                 Midlands      5
## 393  2020-06-27                 Midlands      5
## 394  2020-06-28                 Midlands      7
## 395  2020-06-29                 Midlands      6
## 396  2020-06-30                 Midlands      6
## 397  2020-07-01                 Midlands      7
## 398  2020-07-02                 Midlands      9
## 399  2020-07-03                 Midlands      3
## 400  2020-07-04                 Midlands      4
## 401  2020-07-05                 Midlands      6
## 402  2020-07-06                 Midlands      5
## 403  2020-07-07                 Midlands      3
## 404  2020-07-08                 Midlands      5
## 405  2020-07-09                 Midlands      8
## 406  2020-07-10                 Midlands      3
## 407  2020-07-11                 Midlands      0
## 408  2020-07-12                 Midlands      5
## 409  2020-07-13                 Midlands      1
## 410  2020-07-14                 Midlands      0
## 411  2020-07-15                 Midlands      1
## 412  2020-03-01 North East and Yorkshire      0
## 413  2020-03-02 North East and Yorkshire      0
## 414  2020-03-03 North East and Yorkshire      0
## 415  2020-03-04 North East and Yorkshire      0
## 416  2020-03-05 North East and Yorkshire      0
## 417  2020-03-06 North East and Yorkshire      0
## 418  2020-03-07 North East and Yorkshire      0
## 419  2020-03-08 North East and Yorkshire      0
## 420  2020-03-09 North East and Yorkshire      0
## 421  2020-03-10 North East and Yorkshire      0
## 422  2020-03-11 North East and Yorkshire      0
## 423  2020-03-12 North East and Yorkshire      0
## 424  2020-03-13 North East and Yorkshire      0
## 425  2020-03-14 North East and Yorkshire      0
## 426  2020-03-15 North East and Yorkshire      2
## 427  2020-03-16 North East and Yorkshire      3
## 428  2020-03-17 North East and Yorkshire      1
## 429  2020-03-18 North East and Yorkshire      2
## 430  2020-03-19 North East and Yorkshire      6
## 431  2020-03-20 North East and Yorkshire      5
## 432  2020-03-21 North East and Yorkshire      6
## 433  2020-03-22 North East and Yorkshire      7
## 434  2020-03-23 North East and Yorkshire      9
## 435  2020-03-24 North East and Yorkshire      8
## 436  2020-03-25 North East and Yorkshire     18
## 437  2020-03-26 North East and Yorkshire     21
## 438  2020-03-27 North East and Yorkshire     28
## 439  2020-03-28 North East and Yorkshire     35
## 440  2020-03-29 North East and Yorkshire     38
## 441  2020-03-30 North East and Yorkshire     64
## 442  2020-03-31 North East and Yorkshire     60
## 443  2020-04-01 North East and Yorkshire     67
## 444  2020-04-02 North East and Yorkshire     75
## 445  2020-04-03 North East and Yorkshire    100
## 446  2020-04-04 North East and Yorkshire    105
## 447  2020-04-05 North East and Yorkshire     92
## 448  2020-04-06 North East and Yorkshire     96
## 449  2020-04-07 North East and Yorkshire    102
## 450  2020-04-08 North East and Yorkshire    107
## 451  2020-04-09 North East and Yorkshire    111
## 452  2020-04-10 North East and Yorkshire    117
## 453  2020-04-11 North East and Yorkshire     98
## 454  2020-04-12 North East and Yorkshire     84
## 455  2020-04-13 North East and Yorkshire     94
## 456  2020-04-14 North East and Yorkshire    107
## 457  2020-04-15 North East and Yorkshire     96
## 458  2020-04-16 North East and Yorkshire    103
## 459  2020-04-17 North East and Yorkshire     88
## 460  2020-04-18 North East and Yorkshire     95
## 461  2020-04-19 North East and Yorkshire     88
## 462  2020-04-20 North East and Yorkshire    100
## 463  2020-04-21 North East and Yorkshire     76
## 464  2020-04-22 North East and Yorkshire     84
## 465  2020-04-23 North East and Yorkshire     63
## 466  2020-04-24 North East and Yorkshire     72
## 467  2020-04-25 North East and Yorkshire     69
## 468  2020-04-26 North East and Yorkshire     65
## 469  2020-04-27 North East and Yorkshire     65
## 470  2020-04-28 North East and Yorkshire     57
## 471  2020-04-29 North East and Yorkshire     69
## 472  2020-04-30 North East and Yorkshire     57
## 473  2020-05-01 North East and Yorkshire     64
## 474  2020-05-02 North East and Yorkshire     48
## 475  2020-05-03 North East and Yorkshire     40
## 476  2020-05-04 North East and Yorkshire     49
## 477  2020-05-05 North East and Yorkshire     40
## 478  2020-05-06 North East and Yorkshire     51
## 479  2020-05-07 North East and Yorkshire     45
## 480  2020-05-08 North East and Yorkshire     42
## 481  2020-05-09 North East and Yorkshire     44
## 482  2020-05-10 North East and Yorkshire     40
## 483  2020-05-11 North East and Yorkshire     29
## 484  2020-05-12 North East and Yorkshire     27
## 485  2020-05-13 North East and Yorkshire     28
## 486  2020-05-14 North East and Yorkshire     31
## 487  2020-05-15 North East and Yorkshire     32
## 488  2020-05-16 North East and Yorkshire     35
## 489  2020-05-17 North East and Yorkshire     26
## 490  2020-05-18 North East and Yorkshire     30
## 491  2020-05-19 North East and Yorkshire     27
## 492  2020-05-20 North East and Yorkshire     22
## 493  2020-05-21 North East and Yorkshire     33
## 494  2020-05-22 North East and Yorkshire     22
## 495  2020-05-23 North East and Yorkshire     18
## 496  2020-05-24 North East and Yorkshire     26
## 497  2020-05-25 North East and Yorkshire     21
## 498  2020-05-26 North East and Yorkshire     21
## 499  2020-05-27 North East and Yorkshire     22
## 500  2020-05-28 North East and Yorkshire     21
## 501  2020-05-29 North East and Yorkshire     25
## 502  2020-05-30 North East and Yorkshire     20
## 503  2020-05-31 North East and Yorkshire     20
## 504  2020-06-01 North East and Yorkshire     17
## 505  2020-06-02 North East and Yorkshire     23
## 506  2020-06-03 North East and Yorkshire     23
## 507  2020-06-04 North East and Yorkshire     17
## 508  2020-06-05 North East and Yorkshire     18
## 509  2020-06-06 North East and Yorkshire     21
## 510  2020-06-07 North East and Yorkshire     14
## 511  2020-06-08 North East and Yorkshire     11
## 512  2020-06-09 North East and Yorkshire     12
## 513  2020-06-10 North East and Yorkshire     19
## 514  2020-06-11 North East and Yorkshire      7
## 515  2020-06-12 North East and Yorkshire      9
## 516  2020-06-13 North East and Yorkshire     10
## 517  2020-06-14 North East and Yorkshire     11
## 518  2020-06-15 North East and Yorkshire      9
## 519  2020-06-16 North East and Yorkshire     10
## 520  2020-06-17 North East and Yorkshire      9
## 521  2020-06-18 North East and Yorkshire     11
## 522  2020-06-19 North East and Yorkshire      6
## 523  2020-06-20 North East and Yorkshire      4
## 524  2020-06-21 North East and Yorkshire      4
## 525  2020-06-22 North East and Yorkshire      6
## 526  2020-06-23 North East and Yorkshire      7
## 527  2020-06-24 North East and Yorkshire     10
## 528  2020-06-25 North East and Yorkshire      4
## 529  2020-06-26 North East and Yorkshire      7
## 530  2020-06-27 North East and Yorkshire      3
## 531  2020-06-28 North East and Yorkshire      5
## 532  2020-06-29 North East and Yorkshire      2
## 533  2020-06-30 North East and Yorkshire      5
## 534  2020-07-01 North East and Yorkshire      1
## 535  2020-07-02 North East and Yorkshire      4
## 536  2020-07-03 North East and Yorkshire      3
## 537  2020-07-04 North East and Yorkshire      4
## 538  2020-07-05 North East and Yorkshire      2
## 539  2020-07-06 North East and Yorkshire      2
## 540  2020-07-07 North East and Yorkshire      3
## 541  2020-07-08 North East and Yorkshire      3
## 542  2020-07-09 North East and Yorkshire      0
## 543  2020-07-10 North East and Yorkshire      3
## 544  2020-07-11 North East and Yorkshire      1
## 545  2020-07-12 North East and Yorkshire      4
## 546  2020-07-13 North East and Yorkshire      1
## 547  2020-07-14 North East and Yorkshire      1
## 548  2020-07-15 North East and Yorkshire      1
## 549  2020-03-01               North West      0
## 550  2020-03-02               North West      0
## 551  2020-03-03               North West      0
## 552  2020-03-04               North West      0
## 553  2020-03-05               North West      1
## 554  2020-03-06               North West      0
## 555  2020-03-07               North West      0
## 556  2020-03-08               North West      1
## 557  2020-03-09               North West      0
## 558  2020-03-10               North West      0
## 559  2020-03-11               North West      0
## 560  2020-03-12               North West      2
## 561  2020-03-13               North West      3
## 562  2020-03-14               North West      1
## 563  2020-03-15               North West      4
## 564  2020-03-16               North West      2
## 565  2020-03-17               North West      4
## 566  2020-03-18               North West      6
## 567  2020-03-19               North West      7
## 568  2020-03-20               North West     10
## 569  2020-03-21               North West     11
## 570  2020-03-22               North West     13
## 571  2020-03-23               North West     15
## 572  2020-03-24               North West     21
## 573  2020-03-25               North West     21
## 574  2020-03-26               North West     29
## 575  2020-03-27               North West     36
## 576  2020-03-28               North West     28
## 577  2020-03-29               North West     46
## 578  2020-03-30               North West     67
## 579  2020-03-31               North West     52
## 580  2020-04-01               North West     86
## 581  2020-04-02               North West     96
## 582  2020-04-03               North West     95
## 583  2020-04-04               North West     98
## 584  2020-04-05               North West    102
## 585  2020-04-06               North West    100
## 586  2020-04-07               North West    135
## 587  2020-04-08               North West    127
## 588  2020-04-09               North West    119
## 589  2020-04-10               North West    117
## 590  2020-04-11               North West    138
## 591  2020-04-12               North West    125
## 592  2020-04-13               North West    129
## 593  2020-04-14               North West    131
## 594  2020-04-15               North West    114
## 595  2020-04-16               North West    135
## 596  2020-04-17               North West     98
## 597  2020-04-18               North West    113
## 598  2020-04-19               North West     71
## 599  2020-04-20               North West     83
## 600  2020-04-21               North West     76
## 601  2020-04-22               North West     86
## 602  2020-04-23               North West     85
## 603  2020-04-24               North West     66
## 604  2020-04-25               North West     66
## 605  2020-04-26               North West     55
## 606  2020-04-27               North West     54
## 607  2020-04-28               North West     57
## 608  2020-04-29               North West     63
## 609  2020-04-30               North West     59
## 610  2020-05-01               North West     45
## 611  2020-05-02               North West     56
## 612  2020-05-03               North West     55
## 613  2020-05-04               North West     48
## 614  2020-05-05               North West     48
## 615  2020-05-06               North West     44
## 616  2020-05-07               North West     49
## 617  2020-05-08               North West     42
## 618  2020-05-09               North West     31
## 619  2020-05-10               North West     42
## 620  2020-05-11               North West     35
## 621  2020-05-12               North West     38
## 622  2020-05-13               North West     25
## 623  2020-05-14               North West     26
## 624  2020-05-15               North West     33
## 625  2020-05-16               North West     32
## 626  2020-05-17               North West     24
## 627  2020-05-18               North West     31
## 628  2020-05-19               North West     35
## 629  2020-05-20               North West     27
## 630  2020-05-21               North West     27
## 631  2020-05-22               North West     26
## 632  2020-05-23               North West     31
## 633  2020-05-24               North West     26
## 634  2020-05-25               North West     31
## 635  2020-05-26               North West     27
## 636  2020-05-27               North West     27
## 637  2020-05-28               North West     28
## 638  2020-05-29               North West     20
## 639  2020-05-30               North West     19
## 640  2020-05-31               North West     13
## 641  2020-06-01               North West     12
## 642  2020-06-02               North West     27
## 643  2020-06-03               North West     22
## 644  2020-06-04               North West     22
## 645  2020-06-05               North West     16
## 646  2020-06-06               North West     26
## 647  2020-06-07               North West     20
## 648  2020-06-08               North West     23
## 649  2020-06-09               North West     17
## 650  2020-06-10               North West     16
## 651  2020-06-11               North West     16
## 652  2020-06-12               North West     11
## 653  2020-06-13               North West     10
## 654  2020-06-14               North West     15
## 655  2020-06-15               North West     16
## 656  2020-06-16               North West     15
## 657  2020-06-17               North West     13
## 658  2020-06-18               North West     13
## 659  2020-06-19               North West      7
## 660  2020-06-20               North West     11
## 661  2020-06-21               North West      7
## 662  2020-06-22               North West     11
## 663  2020-06-23               North West     13
## 664  2020-06-24               North West     13
## 665  2020-06-25               North West     15
## 666  2020-06-26               North West      6
## 667  2020-06-27               North West      7
## 668  2020-06-28               North West      9
## 669  2020-06-29               North West      8
## 670  2020-06-30               North West      6
## 671  2020-07-01               North West      3
## 672  2020-07-02               North West      6
## 673  2020-07-03               North West      6
## 674  2020-07-04               North West      4
## 675  2020-07-05               North West      6
## 676  2020-07-06               North West      9
## 677  2020-07-07               North West      7
## 678  2020-07-08               North West      5
## 679  2020-07-09               North West     10
## 680  2020-07-10               North West      2
## 681  2020-07-11               North West      3
## 682  2020-07-12               North West      0
## 683  2020-07-13               North West      6
## 684  2020-07-14               North West      2
## 685  2020-07-15               North West      1
## 686  2020-03-01               South East      0
## 687  2020-03-02               South East      0
## 688  2020-03-03               South East      1
## 689  2020-03-04               South East      0
## 690  2020-03-05               South East      1
## 691  2020-03-06               South East      0
## 692  2020-03-07               South East      0
## 693  2020-03-08               South East      1
## 694  2020-03-09               South East      1
## 695  2020-03-10               South East      1
## 696  2020-03-11               South East      1
## 697  2020-03-12               South East      0
## 698  2020-03-13               South East      1
## 699  2020-03-14               South East      1
## 700  2020-03-15               South East      5
## 701  2020-03-16               South East      8
## 702  2020-03-17               South East      7
## 703  2020-03-18               South East     10
## 704  2020-03-19               South East      9
## 705  2020-03-20               South East     13
## 706  2020-03-21               South East      7
## 707  2020-03-22               South East     25
## 708  2020-03-23               South East     20
## 709  2020-03-24               South East     22
## 710  2020-03-25               South East     29
## 711  2020-03-26               South East     35
## 712  2020-03-27               South East     34
## 713  2020-03-28               South East     36
## 714  2020-03-29               South East     55
## 715  2020-03-30               South East     58
## 716  2020-03-31               South East     65
## 717  2020-04-01               South East     66
## 718  2020-04-02               South East     55
## 719  2020-04-03               South East     72
## 720  2020-04-04               South East     80
## 721  2020-04-05               South East     82
## 722  2020-04-06               South East     88
## 723  2020-04-07               South East    100
## 724  2020-04-08               South East     83
## 725  2020-04-09               South East    104
## 726  2020-04-10               South East     88
## 727  2020-04-11               South East     88
## 728  2020-04-12               South East     88
## 729  2020-04-13               South East     84
## 730  2020-04-14               South East     65
## 731  2020-04-15               South East     72
## 732  2020-04-16               South East     56
## 733  2020-04-17               South East     86
## 734  2020-04-18               South East     57
## 735  2020-04-19               South East     70
## 736  2020-04-20               South East     87
## 737  2020-04-21               South East     51
## 738  2020-04-22               South East     54
## 739  2020-04-23               South East     57
## 740  2020-04-24               South East     64
## 741  2020-04-25               South East     51
## 742  2020-04-26               South East     51
## 743  2020-04-27               South East     41
## 744  2020-04-28               South East     40
## 745  2020-04-29               South East     47
## 746  2020-04-30               South East     29
## 747  2020-05-01               South East     37
## 748  2020-05-02               South East     36
## 749  2020-05-03               South East     17
## 750  2020-05-04               South East     35
## 751  2020-05-05               South East     29
## 752  2020-05-06               South East     25
## 753  2020-05-07               South East     27
## 754  2020-05-08               South East     26
## 755  2020-05-09               South East     28
## 756  2020-05-10               South East     19
## 757  2020-05-11               South East     25
## 758  2020-05-12               South East     27
## 759  2020-05-13               South East     18
## 760  2020-05-14               South East     32
## 761  2020-05-15               South East     25
## 762  2020-05-16               South East     22
## 763  2020-05-17               South East     18
## 764  2020-05-18               South East     22
## 765  2020-05-19               South East     12
## 766  2020-05-20               South East     22
## 767  2020-05-21               South East     15
## 768  2020-05-22               South East     17
## 769  2020-05-23               South East     21
## 770  2020-05-24               South East     17
## 771  2020-05-25               South East     13
## 772  2020-05-26               South East     19
## 773  2020-05-27               South East     18
## 774  2020-05-28               South East     12
## 775  2020-05-29               South East     21
## 776  2020-05-30               South East      8
## 777  2020-05-31               South East     12
## 778  2020-06-01               South East     11
## 779  2020-06-02               South East     13
## 780  2020-06-03               South East     18
## 781  2020-06-04               South East     11
## 782  2020-06-05               South East     11
## 783  2020-06-06               South East     10
## 784  2020-06-07               South East     12
## 785  2020-06-08               South East      8
## 786  2020-06-09               South East     10
## 787  2020-06-10               South East     11
## 788  2020-06-11               South East      5
## 789  2020-06-12               South East      6
## 790  2020-06-13               South East      7
## 791  2020-06-14               South East      7
## 792  2020-06-15               South East      8
## 793  2020-06-16               South East     13
## 794  2020-06-17               South East      9
## 795  2020-06-18               South East      4
## 796  2020-06-19               South East      7
## 797  2020-06-20               South East      5
## 798  2020-06-21               South East      3
## 799  2020-06-22               South East      2
## 800  2020-06-23               South East      8
## 801  2020-06-24               South East      7
## 802  2020-06-25               South East      5
## 803  2020-06-26               South East      8
## 804  2020-06-27               South East      8
## 805  2020-06-28               South East      6
## 806  2020-06-29               South East      5
## 807  2020-06-30               South East      5
## 808  2020-07-01               South East      2
## 809  2020-07-02               South East      7
## 810  2020-07-03               South East      3
## 811  2020-07-04               South East      5
## 812  2020-07-05               South East      4
## 813  2020-07-06               South East      3
## 814  2020-07-07               South East      5
## 815  2020-07-08               South East      3
## 816  2020-07-09               South East      7
## 817  2020-07-10               South East      3
## 818  2020-07-11               South East      1
## 819  2020-07-12               South East      2
## 820  2020-07-13               South East      4
## 821  2020-07-14               South East      1
## 822  2020-07-15               South East      0
## 823  2020-03-01               South West      0
## 824  2020-03-02               South West      0
## 825  2020-03-03               South West      0
## 826  2020-03-04               South West      0
## 827  2020-03-05               South West      0
## 828  2020-03-06               South West      0
## 829  2020-03-07               South West      0
## 830  2020-03-08               South West      0
## 831  2020-03-09               South West      0
## 832  2020-03-10               South West      0
## 833  2020-03-11               South West      1
## 834  2020-03-12               South West      0
## 835  2020-03-13               South West      0
## 836  2020-03-14               South West      1
## 837  2020-03-15               South West      0
## 838  2020-03-16               South West      0
## 839  2020-03-17               South West      2
## 840  2020-03-18               South West      2
## 841  2020-03-19               South West      4
## 842  2020-03-20               South West      3
## 843  2020-03-21               South West      6
## 844  2020-03-22               South West      7
## 845  2020-03-23               South West      8
## 846  2020-03-24               South West      7
## 847  2020-03-25               South West      9
## 848  2020-03-26               South West     11
## 849  2020-03-27               South West     13
## 850  2020-03-28               South West     21
## 851  2020-03-29               South West     18
## 852  2020-03-30               South West     23
## 853  2020-03-31               South West     23
## 854  2020-04-01               South West     21
## 855  2020-04-02               South West     23
## 856  2020-04-03               South West     30
## 857  2020-04-04               South West     42
## 858  2020-04-05               South West     32
## 859  2020-04-06               South West     34
## 860  2020-04-07               South West     39
## 861  2020-04-08               South West     47
## 862  2020-04-09               South West     24
## 863  2020-04-10               South West     46
## 864  2020-04-11               South West     43
## 865  2020-04-12               South West     23
## 866  2020-04-13               South West     27
## 867  2020-04-14               South West     24
## 868  2020-04-15               South West     32
## 869  2020-04-16               South West     29
## 870  2020-04-17               South West     33
## 871  2020-04-18               South West     25
## 872  2020-04-19               South West     31
## 873  2020-04-20               South West     26
## 874  2020-04-21               South West     26
## 875  2020-04-22               South West     23
## 876  2020-04-23               South West     17
## 877  2020-04-24               South West     19
## 878  2020-04-25               South West     15
## 879  2020-04-26               South West     27
## 880  2020-04-27               South West     13
## 881  2020-04-28               South West     17
## 882  2020-04-29               South West     15
## 883  2020-04-30               South West     26
## 884  2020-05-01               South West      6
## 885  2020-05-02               South West      7
## 886  2020-05-03               South West     10
## 887  2020-05-04               South West     17
## 888  2020-05-05               South West     14
## 889  2020-05-06               South West     19
## 890  2020-05-07               South West     16
## 891  2020-05-08               South West      6
## 892  2020-05-09               South West     11
## 893  2020-05-10               South West      5
## 894  2020-05-11               South West      8
## 895  2020-05-12               South West      7
## 896  2020-05-13               South West      7
## 897  2020-05-14               South West      6
## 898  2020-05-15               South West      4
## 899  2020-05-16               South West      4
## 900  2020-05-17               South West      6
## 901  2020-05-18               South West      4
## 902  2020-05-19               South West      6
## 903  2020-05-20               South West      1
## 904  2020-05-21               South West      9
## 905  2020-05-22               South West      6
## 906  2020-05-23               South West      6
## 907  2020-05-24               South West      3
## 908  2020-05-25               South West      8
## 909  2020-05-26               South West     11
## 910  2020-05-27               South West      5
## 911  2020-05-28               South West     10
## 912  2020-05-29               South West      7
## 913  2020-05-30               South West      3
## 914  2020-05-31               South West      2
## 915  2020-06-01               South West      7
## 916  2020-06-02               South West      2
## 917  2020-06-03               South West      7
## 918  2020-06-04               South West      2
## 919  2020-06-05               South West      2
## 920  2020-06-06               South West      1
## 921  2020-06-07               South West      3
## 922  2020-06-08               South West      3
## 923  2020-06-09               South West      0
## 924  2020-06-10               South West      1
## 925  2020-06-11               South West      2
## 926  2020-06-12               South West      2
## 927  2020-06-13               South West      2
## 928  2020-06-14               South West      0
## 929  2020-06-15               South West      2
## 930  2020-06-16               South West      2
## 931  2020-06-17               South West      0
## 932  2020-06-18               South West      0
## 933  2020-06-19               South West      0
## 934  2020-06-20               South West      2
## 935  2020-06-21               South West      0
## 936  2020-06-22               South West      1
## 937  2020-06-23               South West      1
## 938  2020-06-24               South West      1
## 939  2020-06-25               South West      0
## 940  2020-06-26               South West      3
## 941  2020-06-27               South West      0
## 942  2020-06-28               South West      0
## 943  2020-06-29               South West      1
## 944  2020-06-30               South West      0
## 945  2020-07-01               South West      0
## 946  2020-07-02               South West      0
## 947  2020-07-03               South West      0
## 948  2020-07-04               South West      0
## 949  2020-07-05               South West      1
## 950  2020-07-06               South West      0
## 951  2020-07-07               South West      0
## 952  2020-07-08               South West      2
## 953  2020-07-09               South West      0
## 954  2020-07-10               South West      1
## 955  2020-07-11               South West      0
## 956  2020-07-12               South West      0
## 957  2020-07-13               South West      1
## 958  2020-07-14               South West      0
## 959  2020-07-15               South West      0

1.5 Completion date

We extract the completion date from the NHS Pathways file timestamp:


database_date <- attr(x, "timestamp")
database_date
## [1] "2020-07-16"

The completion date of the NHS Pathways data is Thursday 16 Jul 2020.

1.6 Auxiliary functions

These are functions which will be used further in the analyses.

Function to estimate the generalised R-squared as the proportion of deviance explained by a given model:


## Function to calculate R2 for Poisson model
## not adjusted for model complexity but all models have the same DF here

Rsq <- function(x) {
  1 - (x$deviance / x$null.deviance)
}

Function to extract growth rates per region as well as halving times, and the associated 95% confidence intervals:


## function to extract the coefficients, find the level of the intercept,
## reconstruct the values of r, get confidence intervals

get_r <- function(model) {
  ##  extract coefficients and conf int
  out <- data.frame(r = coef(model))  %>%
    rownames_to_column("var") %>% 
    cbind(confint(model)) %>%
    filter(!grepl("day_of_week", var)) %>% 
    filter(grepl("day", var)) %>%
    rename(lower_95 = "2.5 %",
           upper_95 = "97.5 %") %>%
    mutate(var = sub("day:", "", var))
  
  ## reconstruct values: intercept + region-coefficient
  for (i in 2:nrow(out)) {
    out[i, -1] <- out[1, -1] + out[i, -1]
  }
  
  ## find the name of the intercept, restore regions names
  out <- out %>%
    mutate(nhs_region = model$xlevels$nhs_region) %>%
    select(nhs_region, everything(), -var)
  
  ## find halving times
  halving <- log(0.5) / out[,-1] %>%
    rename(halving_t = r,
           halving_t_lower_95 = lower_95,
           halving_t_upper_95 = upper_95)
  
  ## set halving times with exclusion intervals to NA
  no_halving <- out$lower_95 < 0 & out$upper_95 > 0
  halving[no_halving, ] <- NA_real_
  
  ## return all data
  cbind(out, halving)
  
}

Functions used in the correlation analysis between NHS Pathways reports and deaths:

## Function to calculate Pearson's correlation between deaths and lagged
## reports. Note that `pearson` can be replaced with `spearman` for rank
## correlation.

getcor <- function(x, ndx) {
  return(cor(x$deaths[ndx],
             x$note_lag[ndx],
             use = "complete.obs",
             method = "pearson"))
}

## Catch if sample size throws an error
getcor2 <- possibly(getcor, otherwise = NA)

getboot <- function(x) {
  result <- boot::boot.ci(boot::boot(x, getcor2, R = 1000), 
                           type = "bca")
  return(data.frame(n = sum(!is.na(x$note_lag) & !is.na(x$deaths)),
                    r = result$t0,
                    r_low = result$bca[4],
                    r_hi = result$bca[5]))
}

Function to classify the day of the week into weekend, Monday, and the rest:


## Fn to add day of week
day_of_week <- function(df) {
  df %>% 
    dplyr::mutate(day_of_week = lubridate::wday(date, label = TRUE)) %>% 
    dplyr::mutate(day_of_week = dplyr::case_when(
      day_of_week %in% c("Sat", "Sun") ~ "weekend",
      day_of_week %in% c("Mon") ~ "monday",
      !(day_of_week %in% c("Sat", "Sun", "Mon")) ~ "rest_of_week"
    ) %>% 
      factor(levels = c("rest_of_week", "monday", "weekend")))
}

Custom color palettes, color scales, and vectors of colors:


pal <- c("#006212",
         "#ae3cab",
         "#00db90",
         "#960c00",
         "#55aaff",
         "#ff7e78",
         "#00388d")

age.pal <- viridis::viridis(3,begin = 0.1, end = 0.7)

3 Comparison with deaths time series

3.1 Outline

We want to explore the correlation between NHS Pathways reports and deaths, and assess the potential for reports to be used as an early warning system for disease resurgence.

Death data are publically available. We truncate the time series to avoid bias from reporting delay - we assume a conservative delay of three weeks.

3.2 Lagged correlation

We calculate Pearson’s correlation coefficient between deaths and NHS Pathways notifications using different lags. Confidence intervals are obtained using bootstrap. Note that results were also confirmed using Spearman’s rank correlation.

First we join the NHS Pathways and death data, and aggregate over all England:

## truncate death data for reporting delay
trunc_date <- max(dth$date_report) - delay_max

dth_trunc <- dth %>%
  rename(date = date_report) %>%
  filter(date <= trunc_date) 

## join with notification data
all_data <- x %>% 
  filter(!is.na(nhs_region)) %>%
  group_by(date, nhs_region) %>%
  summarise(count = sum(count, na.rm = T)) %>%
  ungroup %>%
  inner_join(dth_trunc,
             by = c("date","nhs_region"))

all_tot <- all_data %>%
  group_by(date) %>%
  summarise(count = sum(count, na.rm = TRUE),
            deaths = sum(deaths, na.rm = TRUE)) 

We calculate correlation with lagged NHS Pathways reports from 0 to 30 days behind deaths:


## Calculate all correlations + bootstrap CIs
lag_cor <- data.frame()
for (i in 0:30) {
  
  ## lag reports
  summary <- all_tot %>% 
    mutate(note_lag = lag(count, i)) %>%
    ## calculate rank correlation and bootstrap CI
    getboot(.) %>%
    mutate(lag = i)

  lag_cor <- bind_rows(lag_cor, summary)
}

cor_vs_lag <- ggplot(lag_cor, aes(lag, r)) +
  theme_bw() +
  geom_ribbon(aes(ymin = r_low, ymax = r_hi), alpha = 0.2) +
  geom_hline(yintercept = 0, lty = "longdash") +
  geom_point() +
  geom_line() +
  labs(x = "Lag between NHS pathways and death data (days)",
       y = "Pearson's correlation") +
  large_txt
cor_vs_lag


l_opt <- which.max(lag_cor$r)

This analysis suggests that the best lag is 23 days. We then compare and plot the number of deaths reported against the number of NHS Pathways reports lagged by 23 days.


all_tot <- all_tot %>%
  rename(date_death = date) %>%
  mutate(note_lag = lag(count, lag_cor$lag[l_opt]),
         note_lag_c = (note_lag - mean(note_lag, na.rm = T)),
         date_note = lag(date_death,16))

lag_mod <- glm(deaths ~ note_lag, data = all_tot, family = "quasipoisson")

summary(lag_mod)
## 
## Call:
## glm(formula = deaths ~ note_lag, family = "quasipoisson", data = all_tot)
## 
## Deviance Residuals: 
##      Min        1Q    Median        3Q       Max  
## -13.1961   -4.1881   -0.2234    3.8028    8.2223  
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 4.604e+00  6.417e-02   71.75   <2e-16 ***
## note_lag    1.447e-05  6.675e-07   21.67   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for quasipoisson family taken to be 23.61847)
## 
##     Null deviance: 12015.1  on 75  degrees of freedom
## Residual deviance:  1846.3  on 74  degrees of freedom
##   (23 observations deleted due to missingness)
## AIC: NA
## 
## Number of Fisher Scoring iterations: 4

exp(coefficients(lag_mod))
## (Intercept)    note_lag 
##   99.898121    1.000014
exp(confint(lag_mod))
##                 2.5 %     97.5 %
## (Intercept) 87.919137 113.070812
## note_lag     1.000013   1.000016

Rsq(lag_mod)
## [1] 0.8463367

mod_fit <- as.data.frame(predict(lag_mod, type = "link", se.fit = TRUE)[1:2])

all_tot_pred <- 
  all_tot %>%
  filter(!is.na(note_lag)) %>%
  mutate(pred = mod_fit$fit,
         pred.se = mod_fit$se.fit,
         low = exp(pred - 1.96*pred.se),
         hi = exp(pred + 1.96*pred.se))


glm_fit <- all_tot_pred %>% 
    filter(!is.na(note_lag)) %>%
  ggplot(aes(x = note_lag, y = deaths)) +
  geom_point() + 
  geom_line(aes(y = exp(pred))) + 
  geom_ribbon(aes(ymin = low, ymax = hi), alpha = 0.3, col = "grey") +
  theme_bw() +
  labs(y = "Daily number of\ndeaths reported",
       x = "Daily number of NHS Pathways reports") +
  large_txt

glm_fit

4 Supplementary figures

4.1 Serial interval distribution

This is a comparison of gamma versus lognormal distribution for the serial interval used to convert r to R in our analysis. Both distributions are parameterised with mean 4.7 and standard deviation 2.9.

SI_param <- epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
                                        shape = SI_param$shape,
                                        scale = SI_param$scale, w = 0.5)

SI_distribution2 <- distcrete::distcrete("lnorm", interval = 1,
                                        meanlog = log(4.7),
                                        sdlog = log(2.9), w = 0.5)

SI_dist1 <- data.frame(x = SI_distribution$r(1e5)) 
SI_dist1 <- count(SI_dist1, x) %>%
    ggplot() +
    geom_col(aes(x = x, y = n)) +
    labs(x = "Serial interval (days)", y = "Frequency") +
    scale_x_continuous(breaks = seq(0, 30, 5)) +
    theme_bw()

SI_dist2 <- data.frame(x = SI_distribution2$r(1e5)) 
SI_dist2 <- count(SI_dist2, x) %>%
    ggplot() +
    geom_col(aes(x = x, y = n)) +
    labs(x = "Serial interval (days)", y = "Frequency") +
    scale_x_continuous(breaks = seq(0, 200, 20), limits = c(0, 200)) +
    theme_bw()


ggpubr::ggarrange(SI_dist1,
                  SI_dist2,
                  nrow = 1,
                  labels = "AUTO") 

4.2 Sensitivity analysis - 7 or 21 days moving window

We reproduce the window analysis with either a 7 or 21 days window for sensitivity purposes.

First with the 7 days window:

## set moving time window (1/2/3 weeks)
w <- 7

# create empty df
r_all_sliding_7days <- NULL

## make data for model
x_model_all_moving <- x %>%
  filter(!is.na(nhs_region)) %>% 
  group_by(date, nhs_region) %>%
  summarise(n = sum(count)) 

unique_dates <- unique(x_model_all_moving$date)

for (i in 1:(length(unique_dates) - w)) {
  
  date_i <- unique_dates[i]
  
  date_i_max <- date_i + w
  
  model_data <- x_model_all_moving %>%
    filter(date >= date_i & date < date_i_max) %>%
    mutate(day = as.integer(date - date_i)) %>% 
    day_of_week()
  
  
  mod <- glm(n ~ day * nhs_region + day_of_week,
             data = model_data,
             family = 'quasipoisson')
  
  # get growth rate
  r <- get_r(mod)
  r$w_min <- date_i
  r$w_max <- date_i_max
  
  # combine all estimates
  r_all_sliding_7days <- bind_rows(r_all_sliding_7days, r)
  
}

#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
                                        shape = SI_param$shape,
                                        scale = SI_param$scale,
                                        w = 0.5)

#convert growth rates r to R0
r_all_sliding_7days <- r_all_sliding_7days %>%
  mutate(R = epitrix::r2R0(r, SI_distribution),
         R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
         R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))
# plot
plot_growth <-
  r_all_sliding_7days %>%
  ggplot(aes(x = w_max, y = r)) +
  geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
  geom_line(aes(colour = nhs_region)) +
  geom_point(aes(colour = nhs_region)) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  theme_bw() +
  scale_weeks +
  theme(legend.position = "bottom",
        plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
  guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
  labs(x = "",
       y = "Estimated daily growth rate (r)") +
  scale_colour_manual(values = pal)
plot_R <- r_all_sliding_7days %>%
  ggplot(aes(x = w_max, y = R)) +
  geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
  geom_line(aes(colour = nhs_region)) +
  geom_point(aes(colour = nhs_region)) +
  geom_hline(yintercept = 1, linetype = "dashed") +
  theme_bw() +
  scale_weeks +
  theme(legend.position = "bottom",
        plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
  guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
  labs(x = "",
       y = "Estimated effective reproduction\nnumber (Re)") +
  scale_colour_manual(values = pal)

R <- r_all_sliding_7days %>%
  mutate(lower_95 = R_lower_95, 
         upper_95 = R_upper_95,
         value = R,
         measure = "R",
         reference = 1)

r_R <- r_all_sliding_7days %>%
  mutate(measure = "r",
         value = r,
         reference = 0) %>%
  bind_rows(R)

r_R_7 <- r_R %>%
  ggplot(aes(x = w_max, y = value)) +
  geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
  geom_line(aes(colour = nhs_region)) +
  geom_point(aes(colour = nhs_region)) +
  geom_hline(aes(yintercept = reference), linetype = "dashed") +
  theme_bw() +
  scale_weeks +
  theme(legend.position = "bottom",
        plot.margin = margin(0.5,1,0,0, "cm"),
        strip.background = element_blank(),
        strip.placement = "outside"
  ) +
  guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
  labs(x = "", y = "") +
  scale_colour_manual(values = pal) +
  facet_grid(rows = vars(measure),
             scales = "free_y",
             switch = "y",
             labeller = as_labeller(c(r = "Daily growth rate (r)",
                                      R = "Effective reproduction\nnumber (Re)")))

Then with the 21 days window:

## set moving time window (1/2/3 weeks)
w <- 21

# create empty df
r_all_sliding_21days <- NULL

## make data for model
x_model_all_moving <- x %>%
  filter(!is.na(nhs_region)) %>% 
  group_by(date, nhs_region) %>%
  summarise(n = sum(count)) 

unique_dates <- unique(x_model_all_moving$date)

for (i in 1:(length(unique_dates) - w)) {
  
  date_i <- unique_dates[i]
  
  date_i_max <- date_i + w
  
  model_data <- x_model_all_moving %>%
    filter(date >= date_i & date < date_i_max) %>%
    mutate(day = as.integer(date - date_i)) %>% 
    day_of_week()
  
  
  mod <- glm(n ~ day * nhs_region + day_of_week,
             data = model_data,
             family = 'quasipoisson')
  
  # get growth rate
  r <- get_r(mod)
  r$w_min <- date_i
  r$w_max <- date_i_max
  
  # combine all estimates
  r_all_sliding_21days <- bind_rows(r_all_sliding_21days, r)
  
}

#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
                                        shape = SI_param$shape,
                                        scale = SI_param$scale,
                                        w = 0.5)

#convert growth rates r to R0
r_all_sliding_21days <- r_all_sliding_21days %>%
  mutate(R = epitrix::r2R0(r, SI_distribution),
         R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
         R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))
# plot
plot_growth <-
  r_all_sliding_21days %>%
  ggplot(aes(x = w_max, y = r)) +
  geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
  geom_line(aes(colour = nhs_region)) +
  geom_point(aes(colour = nhs_region)) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  theme_bw() +
  scale_weeks +
  theme(legend.position = "bottom",
        plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
  guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
  labs(x = "",
       y = "Estimated daily growth rate (r)") +
  scale_colour_manual(values = pal)
# plot
plot_R <-
  r_all_sliding_21days %>%
  ggplot(aes(x = w_max, y = R)) +
  geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
  geom_line(aes(colour = nhs_region)) +
  geom_point(aes(colour = nhs_region)) +
  geom_hline(yintercept = 1, linetype = "dashed") +
  theme_bw() +
  scale_weeks +
  theme(legend.position = "bottom",
        plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
  guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
  labs(x = "",
       y = "Estimated effective reproduction\nnumber (Re)") +
  scale_colour_manual(values = pal)

R <- r_all_sliding_21days %>%
  mutate(lower_95 = R_lower_95, 
         upper_95 = R_upper_95,
         value = R,
         measure = "R",
         reference = 1)

r_R <- r_all_sliding_21days %>%
  mutate(measure = "r",
         value = r,
         reference = 0) %>%
  bind_rows(R)

r_R_21 <- r_R %>%
  ggplot(aes(x = w_max, y = value)) +
  geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
  geom_line(aes(colour = nhs_region)) +
  geom_point(aes(colour = nhs_region)) +
  geom_hline(aes(yintercept = reference), linetype = "dashed") +
  theme_bw() +
  scale_weeks +
  theme(legend.position = "bottom",
        plot.margin = margin(0.5,1,0,0, "cm"),
        strip.background = element_blank(),
        strip.placement = "outside"
  ) +
  guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
  labs(x = "", y = "") +
  scale_colour_manual(values = pal) +
  facet_grid(rows = vars(measure),
             scales = "free_y",
             switch = "y",
             labeller = as_labeller(c(r = "Daily growth rate (r)",
                                      R = "Effective reproduction\nnumber (Re)")))

And we combine both outputs into a single plot:


ggpubr::ggarrange(r_R_7,
                  r_R_21,
                  nrow = 2,
                  labels = "AUTO",
                  common.legend = TRUE,
                  legend = "bottom") 

4.3 Correlation between NHS Pathways reports and deaths by NHS region


lag_cor_reg <- data.frame()

for (i in 0:30) {

  summary <-
    all_data %>%
    group_by(nhs_region) %>%
    mutate(note_lag = lag(count, i)) %>%
    ## calculate rank correlation and bootstrap CI for each region
    group_modify(~getboot(.x)) %>%
    mutate(lag = i)
  
  lag_cor_reg <- bind_rows(lag_cor_reg, summary)
}

cor_vs_lag_reg <- 
lag_cor_reg %>%
ggplot(aes(lag, r, col = nhs_region)) +
  geom_hline(yintercept = 0, lty = "longdash") +
  geom_ribbon(aes(ymin = r_low, ymax = r_hi, col = NULL, fill = nhs_region), alpha = 0.2) +
  geom_point() +
  geom_line() +
  facet_wrap(~nhs_region) +
  scale_color_manual(values = pal) +
  scale_fill_manual(values = pal, guide = F) +  
  theme_bw() +
  labs(x = "Lag between NHS pathways and death data (days)", y = "Pearson's correlation", col = "NHS region") +
  theme(legend.position = "bottom") +
  guides(color = guide_legend(override.aes = list(fill = NA)))

cor_vs_lag_reg

5 Export data

We save the tables created during our analysis:


if (!dir.exists("excel_tables")) {
  dir.create("excel_tables")
}


## list all tables, and loop over export
tables_to_export <- c("r_all_sliding", "lag_cor")

for (e in tables_to_export) {
  rio::export(get(e),
              file.path("excel_tables",
                        paste0(e, ".xlsx")))
}

## also export result from regression on lagged data 
rio::export(lag_mod, file.path("excel_tables", "lag_mod.rds"))

6 System information

6.1 Outline

The following information documents the system on which the document was compiled.

6.2 System

This provides information on the operating system.

Sys.info()
##                                                                                            sysname 
##                                                                                           "Darwin" 
##                                                                                            release 
##                                                                                           "19.5.0" 
##                                                                                            version 
## "Darwin Kernel Version 19.5.0: Tue May 26 20:41:44 PDT 2020; root:xnu-6153.121.2~2/RELEASE_X86_64" 
##                                                                                           nodename 
##                                                                                "Mac-1594976917927" 
##                                                                                            machine 
##                                                                                           "x86_64" 
##                                                                                              login 
##                                                                                             "root" 
##                                                                                               user 
##                                                                                           "runner" 
##                                                                                     effective_user 
##                                                                                           "runner"

6.3 R environment

This provides information on the version of R used:

R.version
##                _                           
## platform       x86_64-apple-darwin17.0     
## arch           x86_64                      
## os             darwin17.0                  
## system         x86_64, darwin17.0          
## status                                     
## major          4                           
## minor          0.2                         
## year           2020                        
## month          06                          
## day            22                          
## svn rev        78730                       
## language       R                           
## version.string R version 4.0.2 (2020-06-22)
## nickname       Taking Off Again

6.4 R packages

This provides information on the packages used:

sessionInfo()
## R version 4.0.2 (2020-06-22)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Catalina 10.15.5
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] ggnewscale_0.4.1     ggpubr_0.4.0         lubridate_1.7.9     
##  [4] chngpt_2020.5-21     cyphr_1.1.0          DT_0.14             
##  [7] kableExtra_1.1.0     janitor_2.0.1        remotes_2.1.1       
## [10] projections_0.5.1    earlyR_0.0.1         epitrix_0.2.2       
## [13] distcrete_1.0.3      incidence_1.7.1      rio_0.5.16          
## [16] reshape2_1.4.4       rvest_0.3.5          xml2_1.3.2          
## [19] linelist_0.0.40.9000 forcats_0.5.0        stringr_1.4.0       
## [22] dplyr_1.0.0          purrr_0.3.4          readr_1.3.1         
## [25] tidyr_1.1.0          tibble_3.0.3         ggplot2_3.3.2       
## [28] tidyverse_1.3.0      here_0.1             reportfactory_0.0.5 
## 
## loaded via a namespace (and not attached):
##  [1] nlme_3.1-148      fs_1.4.2          webshot_0.5.2     httr_1.4.1       
##  [5] rprojroot_1.3-2   tools_4.0.2       backports_1.1.8   utf8_1.1.4       
##  [9] R6_2.4.1          mgcv_1.8-31       DBI_1.1.0         colorspace_1.4-1 
## [13] withr_2.2.0       gridExtra_2.3     tidyselect_1.1.0  sodium_1.1       
## [17] curl_4.3          compiler_4.0.2    cli_2.0.2         labeling_0.3     
## [21] matchmaker_0.1.1  scales_1.1.1      digest_0.6.25     foreign_0.8-80   
## [25] rmarkdown_2.3     pkgconfig_2.0.3   htmltools_0.5.0   dbplyr_1.4.4     
## [29] htmlwidgets_1.5.1 rlang_0.4.7       readxl_1.3.1      rstudioapi_0.11  
## [33] farver_2.0.3      generics_0.0.2    jsonlite_1.7.0    crosstalk_1.1.0.1
## [37] car_3.0-8         zip_2.0.4         magrittr_1.5      kyotil_2019.11-22
## [41] Matrix_1.2-18     Rcpp_1.0.5        munsell_0.5.0     fansi_0.4.1      
## [45] viridis_0.5.1     abind_1.4-5       lifecycle_0.2.0   stringi_1.4.6    
## [49] yaml_2.2.1        carData_3.0-4     snakecase_0.11.0  MASS_7.3-51.6    
## [53] plyr_1.8.6        grid_4.0.2        blob_1.2.1        crayon_1.3.4     
## [57] lattice_0.20-41   cowplot_1.0.0     splines_4.0.2     haven_2.3.1      
## [61] hms_0.5.3         knitr_1.29        pillar_1.4.6      boot_1.3-25      
## [65] ggsignif_0.6.0    reprex_0.3.0      glue_1.4.1        evaluate_0.14    
## [69] data.table_1.12.8 modelr_0.1.8      vctrs_0.3.2       selectr_0.4-2    
## [73] cellranger_1.1.0  gtable_0.3.0      assertthat_0.2.1  xfun_0.15        
## [77] openxlsx_4.1.5    broom_0.7.0       rstatix_0.6.0     survival_3.1-12  
## [81] viridisLite_0.3.0 ellipsis_0.3.1